I’d like to learn about probability theory, measure theory and finally machine learning. Where do I start? [closed]

I’d like to learn about probability theory, measure theory and finally machine learning. My ultimate goal is to use machine learning in a piece of software.

I studied calculus and very basic probability in college but that’s pretty much it. Do you know some online courses or books that I could use to learn about these subjects. I’ve found many resources on the web but they all seem targeted to an expert audience. I know it’s going to take some time but where do I start if I’d like to learn from the beginning?

I think there exists two very good and popular references for you (I started with these ones as well having a background of master in actuarial science):

1. An Introduction to Statistical Learning (with application in R) by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani. It is freely available on the site, pretty comprehensive and easy to understand with pratical examples. You can start learning many things even without a very strong statistical background, this reference is good for various profils and includes adequate number of popular algorithms together with its implementation in R without going deep into the mathematical details.
2. The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, Jerome Friedman. Comparing to the first one, this book goes deeper into the mathematical aspects if you want to explore further on the particular algorithms that you find useful for you. (is is free as well)

And of course Cross Validated is one of the best sources where you can learn many things, for me: best pratices, statistical misunderstanding and misuse, and many more. After several years of learning at schools / universities as well as seft-learning, I found that my knownledge is too limited when I first went to Cross Validated. I continue to go here every day since the first visit and learn so much.

引用自：https://stats.stackexchange.com/questions/231092